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Record W4409663591 · doi:10.1159/000545339

Is the Risk of Developing a Crohn’s Disease Increased after Appendectomy? A Systematic Review of the Literature and Meta-Analysis

2025· review· en· W4409663591 on OpenAlexaboutno aff
Isabelle Uhe, Eleftherios Gialamas, Christophe Combescure, Christian Toso, Émilie Liot, G. Meurette, Frédéric Ris, Jérémy Meyer

Bibliographic record

VenueDigestive Surgery · 2025
Typereview
Languageen
FieldMedicine
TopicAppendicitis Diagnosis and Management
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineOdds ratioMeta-analysisInternal medicineCohort studyCrohn's diseaseRelative riskRisk factorConfidence intervalMEDLINEDisease

Abstract

fetched live from OpenAlex

INTRODUCTION: The effect of appendectomy on the development of Crohn's disease (CD) is a matter of debate. The aim of this systematic review and meta-analysis was to gather the latest published data to determine whether patients with a history of appendectomy have an increased risk of developing CD or not. METHODS: MEDLINE, Embase, and the Cochrane Central Register of Controlled Trials were searched for case-control and cohort studies assessing the risk of developing CD after appendectomy. The pooled adjusted and not adjusted odds ratio (OR) with 95% confidence intervals (CIs) were calculated for case-control studies. Heterogeneity was assessed. Studies were ranked using the Newcastle-Ottawa Scale (NOS) and were all of good quality. RESULTS: Fourteen case-control studies and 6 cohort studies were included. Meta-analysis of case-control studies (33,243 patients) of raw OR shows a positive association between appendectomy and CD (OR: 1.51, 95% CI: 0.97-2.36, I2 = 87%), which was not statistically significant (p = 0.069). The meta-analysis of adjusted OR shows that appendectomy represents a statistically significant risk factor for the development of CD (OR: 1.86, 95% CI: 1.01-3.45, p = 0.047, I2 = 89%). CONCLUSION: Appendectomy appears to be a risk factor for the development of CD. However, the discrepant results obtained by meta-analysis of unadjusted OR, the heterogeneity between studies, and the lack of precision of the magnitude of the association mandate confirmation by a large epidemiological study.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.020
metaresearch head score (Gemma)0.049
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.025
Threshold uncertainty score0.108

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0200.049
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0250.041
Bibliometrics0.0090.010
Science and technology studies0.0010.001
Scholarly communication0.0040.002
Open science0.0020.001
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0030.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.045
GPT teacher head0.325
Teacher spread0.281 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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